CIO Business Intelligence

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Check out our list of top big data and data analytics certifications.)

Data Science 124

Data Science Machine Learning Predictive Modeling Experimentation 124

Smart Data Collective

SEPTEMBER 25, 2019

Big data has been billed as being the future of business for quite some time. Analysts have found that the market for big data jobs increased 23% between 2014 and 2019. The impact of big data is felt across all sectors of the economy. However, the future is now. Choose a Career. Learn How To Be Practical.

Big Data 80

Big Data Data Science Predictive Modeling Marketing 80

DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. When business decisions are made based on bad models, the consequences can be severe. When business decisions are made based on bad models, the consequences can be severe.

Risk 111

Risk Modeling IT Risk Management 111

Smart Data Collective

MARCH 3, 2021

The legal sector is still in its infancy when it comes to big data and analytics. Using analytics implies utilizing data to supplement the knowledge, judgement, and experience in the decision-making process and evaluating the situations from a new perspective. Big data can help lawyers chose cases.

Analytics 126

Analytics Big Data Predictive Modeling Insurance 126

Rocket-Powered Data Science

JULY 13, 2023

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 167

Analytics Machine Learning Data Science Deep Learning 167

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. Without big data in predictive analytics, these descriptive models can’t offer a competitive advantage or negotiate future outcomes.

Predictive Analytics 121

Predictive Analytics Analytics Predictive Modeling Data mining 121

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Financial services: Develop credit risk models. from 2022 to 2028.

Predictive Analytics 134

Predictive Analytics Analytics Predictive Modeling Forecasting 134

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 72

Risk Modeling Management Metadata 72

O'Reilly on Data

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Machine Learning 243

Machine Learning Testing Modeling Cost-Benefit 243

IBM Big Data Hub

JANUARY 25, 2024

Yet many AI creators are currently facing backlash for the biases, inaccuracies and problematic data practices being exposed in their models. The math demonstrates a powerful truth All predictive models, including AI, are more accurate when they incorporate diverse human intelligence and experience.

Predictive Modeling 85

Predictive Modeling Modeling Risk Statistics 85

Rocket-Powered Data Science

SEPTEMBER 20, 2021

The data scientists need to find the right data as inputs for their models — they also need a place to write-back the outputs of their models to the data repository for other users to access. How data are stored, labeled, and meta-tagged in the data cloud is no longer a bottleneck to discovery and access.

Data Science 286

Data Science Forecasting Business Intelligence Sales 286

BizAcuity

APRIL 1, 2023

1] With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. There are a number of open-source ML platforms like KNIME that can also be leveraged to detect and predict suspicious behavior.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

IBM Big Data Hub

NOVEMBER 29, 2023

.” No-code and low-code solutions for time series data exploration IBM introduced Downer to the realm where no-code and low-code solutions could build predictive models to provide faster insights. Downer was able to streamline modeling times with watsonx.ai

Predictive Modeling 65

Predictive Modeling Data-driven Data Science Forecasting 65

BizAcuity

JANUARY 18, 2023

With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. Predictive modeling for flagging suspicious activity. Steps to building a highly accurate predictive model for AML.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CIO Business Intelligence

APRIL 22, 2022

For more details on data science bootcamps, see “ 15 best data science bootcamps for boosting your career.”. Data science certifications. Organizations need data scientists and analysts with expertise in techniques for analyzing data. Data science teams. Data science is generally a team discipline.

Data Science 135

Data Science Statistics Machine Learning Visualization 135

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. The model and the data specification become more important than the code.

Machine Learning 343

Machine Learning Statistics Data Quality Modeling 343

CIO Business Intelligence

OCTOBER 13, 2023

For most companies, AI systems rely on large datasets, which require the expertise of data scientists to navigate. It’s a role that requires experience with natural language processing , coding languages, statistical models, and large language and generative AI models.

Deep Learning 142

Deep Learning Machine Learning Modeling Software 142

Smart Data Collective

MARCH 28, 2022

There are four main types of data analytics: Predictive data analytics: It is used to identify various trends, causation, and correlations. It can be further classified as statistical and predictive modeling, but the two are closely associated with each other.

Data Analytics 85

Data Analytics Software Analytics Statistics 85

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 78

Data Science Data Analytics Prescriptive Analytics Analytics 78

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics and data science are closely related.

Data Analytics 123

Data Analytics Diagnostic Analytics Management Analytics 123

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? It’s also necessary to understand data cleaning and processing techniques.

Machine Learning 55

Machine Learning Data Science Statistics Deep Learning 55

IBM Big Data Hub

APRIL 5, 2024

Asset health monitoring defines asset health indexes to rank the asset conditions based on degradation models, failures, overdue preventive work and any other relevant parameters that reflect the health of the assets. Predict functionality builds predictive models to predict imminent failures and calculate assets’ remaining useful life.

Management 66

Management Risk Optimization Predictive Modeling 66

Smart Data Collective

AUGUST 7, 2019

Big data has the power to transform any small business. One study found that 77% of small businesses don’t even have a big data strategy. If your company lacks a big data strategy, then you need to start developing one today. Using Big Data to Fix Your Biggest Problems as a Business Owner.

Data Analytics 100

Data Analytics Analytics Big Data Data Lake 100

Rocket-Powered Data Science

JULY 6, 2021

2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Data integration and cleaning.

Machine Learning 255

Machine Learning Data Quality Statistics Modeling 255

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI in commerce—such as models trained on inadequate or inappropriate data—lead to bad experiences that alienate consumers and businesses. AI models analyze vast amounts of data quickly and accurately.

B2B 66

B2B Interactive Optimization Forecasting 66

IBM Big Data Hub

MAY 18, 2023

This report outlines the combination of traditional decision automation tools with machine learning models and other technologies. It provides a low-code environment where business experts can manage decision automation projects and apply their knowledge to model decisions without extensive coding or deep AI knowledge.

Reporting 89

Reporting Scorecard Predictive Modeling Machine Learning 89

Domino Data Lab

JULY 28, 2021

Data science is a field that uses math and statistics as part of a scientific process to develop an algorithm that can extract insights from data. All models are not made equal. Universally, models have a basis in statistics and probability, from linear regression to decision trees to support vector machines.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. In our world of Big Data, marketers no longer need to simply rely on their gut instincts to make marketing decisions.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

IBM Big Data Hub

APRIL 1, 2024

With IBM watsonx™ Assistant, companies can build large language models and train them using proprietary information, all while helping to ensure the security of their data. Through IBM® watsonx.ai™, various industry-leading models are available for different types of summarization.

Predictive Analytics 79

Predictive Analytics Sales Enterprise Predictive Modeling 79

IBM Big Data Hub

AUGUST 22, 2023

It uses real-world data (both real time and historical) combined with engineering, simulation or machine learning (ML) models to enhance operations and support human decision-making. Traditional AI models versus foundation models These capabilities can help to continuously determine the state of the physical object.

Unstructured Data 75

Unstructured Data Consulting Visualization IoT 75

Rocket-Powered Data Science

OCTOBER 6, 2023

In these applications, the data science involvement includes both the “learning” of the most significant patterns to alert on and the improvement of their models (logic) to minimize false positives and false negatives. Broken models are definitely disruptive to analytics applications and business operations.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

Smart Data Collective

JULY 10, 2019

Big data is changing the nature of healthcare. One of the biggest developments was the implementation of the Medical Information Mart for Intensive Care , which took data from 50,000 patients dating back to 2001. Big data will have an even more profound impact in the near future.

Big Data 71

Big Data Measurement Predictive Modeling Manufacturing 71

IBM Big Data Hub

MAY 1, 2023

The early versions of AI were capable of predictive modelling (e.g., The four categories of predictive modelling, robotics, speech and image recognition are collectively known as algorithm-based AI or Discriminative AI. recommending similar Netflix shows based on your previous choices) or robotics (e.g.,

Insurance 77

Insurance Predictive Modeling Cost-Benefit Statistics 77

CIO Business Intelligence

JUNE 20, 2022

Otis One’s cloud-native platform is built on Microsoft Azure and taps into a Snowflake data lake. IoT sensors send elevator data to the cloud platform, where analytics are applied to support business operations, including reporting, data visualization, and predictive modeling. based company’s elevators smarter.

Internet of Things 104

Internet of Things IoT Manufacturing Data Lake 104

Domino Data Lab

OCTOBER 7, 2020

Danger of Big Data. Big data is the rage. This could be lots of rows (samples) and few columns (variables) like credit card transaction data, or lots of columns (variables) and few rows (samples) like genomic sequencing in life sciences research. Data Has Properties. P >> N) ).

Statistics 145

Statistics Testing Predictive Modeling Modeling 145